1. Field of the Invention
The present invention relates generally to parallel distributed computer systems for simulating neuronal networks that perform neural computations, such as visual perception and motor control.
2. Description of Related Art
Most neuronal models and systems consist of networks of simple units, called neurons, which interact with each other and with the external world via connections called synapses. The information processing in such neuronal systems is carried out in parallel.
There are many specialized software tools that help neuroscientists to simulate models of neural systems. These tools include NEURON, GENESIS, NEST, BRIAN, and many other freely available software tools that simulate biologically plausible and anatomically realistic models. These tools are designed with the view to make the design of such models convenient for neuroscientists. However, the tools are cumbersome to be used to design optimized software or hardware engines to simulate such models efficiently, especially when real-time performance is required, as in autonomous robotics applications.
In contrast, there are many low-level languages, such as assembly languages, LLVM (low-level virtual machine) language, Java Bytecode, chip instruction sets, etc., that are designed for efficient hardware implementations on x86, ARM, and other silicon chips. However, such languages are ill appropriate for parallel simulations of neuronal systems, mostly because the silicon chips are not designed for such parallel neuronal simulations.
There is obviously a need to have parallel hardware architectures and corresponding languages that are optimized for parallel execution and simulation of neuronal models.